ENGSCI 311

Mathematical Modelling 3

Summary


Semester

Semester 2, 2018

Staff

Teaching schedule

Please see Student Services Online for the official class timetable and locations.

Lectures are currently scheduled at:
Mon 11am - 12pm FPAA (260-115)
Tue 9am - 10am FPAA
Thu 9am - 10am FPAA
Fri 11am - 12pm 260-098

Contents


Calendar notes

A selection from: ordinary differential equations, systems of equations, analytical and numerical methods, non-linear ODEs, partial differential equations, separation of variables, numerical methods for solving PDEs, models for optimisation, industrial statistics, data analysis, regression, experimental design reliability methods. Prerequisite: ENGSCI 211Restriction: ENGSCI 313, 314

Outcome mapping


Intended learning outcomes
Related graduate attributes
Related assessments

Models for Optimization: Students will have comprehension of the standard linear, nonlinear and integer programming models. They will be able to model real world problems using these optimization models and solve these using Excel's Solver.

ENGA01: engineering knowledge (4)
ENGA02: problem analysis (2)
ENGA04: investigation (4)
ENGA05: modern tool usage (4)
ENGA10: communication (2)
ENGK02: mathematical modelling (4)
ENGK03: abstraction and formulation (2)
ENGP01: depth of knowledge required (4)
ENGP02: range of conflicting requirements (4)
ENGP03: depth of analysis required (4)
UOA_1: Disciplinary Knowledge and Practice (4)
UOA_2: Critical Thinking (3)
UOA_3: Solution Seeking (2)
UOA_4: Communication and Engagement (2)
UOA_5: Independence and Integrity (2)
MFO Mini-Assignment 1
MFO Test
MFO Mini-Assignment 2
Exam

Data Analysis: Students will have an comprehension of the standard statistical methods of the analysis of variance, the use of linear regression and the development of multiple regression models. They will be able to apply these techniques to analyse the type of data that arises in engineering practice.

ENGA01: engineering knowledge (4)
ENGA02: problem analysis (2)
ENGA04: investigation (4)
ENGA05: modern tool usage (4)
ENGA10: communication (2)
ENGK02: mathematical modelling (4)
ENGK03: abstraction and formulation (2)
ENGP01: depth of knowledge required (4)
ENGP02: range of conflicting requirements (4)
ENGP03: depth of analysis required (4)
UOA_1: Disciplinary Knowledge and Practice (4)
UOA_2: Critical Thinking (3)
UOA_3: Solution Seeking (2)
UOA_4: Communication and Engagement (2)
UOA_5: Independence and Integrity (2)
DA Assignment
Exam

Ordinary Differential Equations: The student will gain knowledge of 1st and 2nd order systems of ODEs and how to solve such systems using eigenvalue and eigenvector methods. The student can apply systems of ODEs theory to analyse signals and solve some signal based problems.

ENGA01: engineering knowledge (4)
ENGA02: problem analysis (2)
ENGK01: theory of natural sciences (4)
ENGK02: mathematical modelling (4)
ENGK03: abstraction and formulation (2)
ENGP01: depth of knowledge required (4)
ENGP02: range of conflicting requirements (4)
ENGP03: depth of analysis required (4)
UOA_1: Disciplinary Knowledge and Practice (4)
UOA_2: Critical Thinking (3)
UOA_3: Solution Seeking (2)
UOA_5: Independence and Integrity (2)
ODE Assignment
Exam

Partial Differential Equations: Knowledge, comprehension and the application of partial differential equations in modelling in engineering science. Students are also required to be able to analyse the results of their models, to synthesise this in terms of the original physical model and to evaluate the usefulness of the model.

ENGA01: engineering knowledge (4)
ENGA02: problem analysis (2)
ENGA04: investigation (4)
ENGA05: modern tool usage (4)
ENGK01: theory of natural sciences (4)
ENGK02: mathematical modelling (4)
ENGK03: abstraction and formulation (2)
ENGP01: depth of knowledge required (4)
ENGP02: range of conflicting requirements (4)
ENGP03: depth of analysis required (4)
UOA_1: Disciplinary Knowledge and Practice (4)
UOA_2: Critical Thinking (3)
UOA_3: Solution Seeking (2)
UOA_5: Independence and Integrity (2)
PDE Assignment
Exam

Assessment


Coursework

3 assignments (ODE, PDE, DA) at 7.5% each
2 mini-assignments (MFO) at 1.5% and 1%
1 test (MFO) at 5%

Exam rules

70% Exam + 30% Coursework (as listed above)

Final percentage may not exceed exam percentage by more than 10%. As with all courses, the final grade is subject to scaling.

The exam is 3 hours long. No calculators are permitted in the exam.

In the event of a student seeking an aegrotat, a greater weight may be placed on the test (reflecting that it is sat under exam conditions). Students who did not complete the test may be required to complete an additional written or oral assessment as part of any aegrotat application.

All queries regarding assignment marks must be made before the exam. No changes in assignment marks are possible once the exam has been sat.

Inclusive learning

Students are urged to discuss privately any impairment-related requirements face-to-face and/or in written form with the course convenor/lecturer and/or tutor.

Other assessment rules

Written assignments are to be submitted via Canvas as PDF files. Assignments may be hand-written and scanned, or typed up and converted to a PDF, or a mix of both.

Assignment Extensions: If you need an extension on an assignment, perhaps because of illness, then please contact the course administrator (details above) as soon as possible. You will need to obtain a medical certificate or other documentation for most extensions.

Note that pressure of work and/or overseas travel are not sufficient reasons to grant extensions or assignment/test exemptions.

Policy on Late Assignment Submissions:

For assignments given as Canvas Quizzes, no late submissions will be accepted. Once the due date / time is past, all active quizzes will be automatically submitted.

For written assignments, aim to have all files safely uploaded well before the due time. It is highly recommended that you upload draft copies of all files at least one day in advance of the deadline, in case of last-minute technical difficulties. Late submissions will be marked as usual, but will be subject to a penalty of 10% (of the total number of marks available) per hour-or-part-thereof. Example Assignment 1 is due at 7pm and is worth 12 marks. A submission received at 19:40pm on the due date would lose 1.2 marks (10% of 12 marks).

Academic integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting his or her learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the world-wide web. A student's assessed work may be reviewed against electronic source material using computerised detection mechanisms. Upon reasonable request, students may be required to provide an electronic version of their work for computerised review.

All students enrolled at the University of Auckland are required to complete a compulsory Academic Integrity course, usually in their first semester/year of enrolment. The University of Auckland’s full guidelines on procedures and penalties for academic dishonesty are available here.

Student feedback


Actions shared/based on previous feedback

Canvas Quizzes, especially as practice / tutorial exercises, were well received and will be continued this year.

This site intends to guide you through your chosen specialisation at the Faculty of Engineering. The semester links lets you view detailed course information for your chosen course. Please note that the structure displayed for your specialisation here will reflect what’s available over the upcoming semesters, but detailed information may be from a previous year.

All the information here is accurate at the time of publication, but you are are advised to additionally consult our official document, the University of Auckland Calendar, for accurate academic regulations, requirements, and policies.